Two connected learning models Explore the linear model at KillChains.com

Evidence and publication

Methodology

KillWebs.com separates current implementation truth, reviewed synthesis, preserved research inputs, public source records, and fictional teaching values. No layer silently upgrades another.

Research basis KW-RPT-001 KW-RPT-014

Authority order

  1. 01

    Current code and visible behavior

    The deployed PHP, data registries, JavaScript, headers, routes, and rendered content define what the site actually does.

  2. 02

    Passing tests and release proof

    Automated checks support claims about syntax, routes, local-only runtime, report hashes, memory pointers, and discovery parity.

  3. 03

    Accepted decisions and architecture

    Current .uai records and reviewed durable documents explain why the implementation has its present shape.

  4. 04

    Reviewed research synthesis

    Public pages promote bounded conclusions that recur across stronger report sources and preserve material uncertainty.

  5. 05

    Preserved reports and proposals

    Full reports remain available as inputs but do not automatically become current fact or product behavior.

Evidence hierarchy

ClassUse on the siteBoundary
Official primary sourceDoctrine, policy, program descriptions, standards, and formal requirementsStill evaluated for date, scope, and what it does not establish
Reviewed analytical reportSynthesis, comparison, questions, architecture implicationsClaims remain qualified and traced to the underlying source class
Interactive explanatory modelMakes relationships and failure modes understandableUses abstract, deterministic teaching values only
Synthetic scenarioDemonstrates tradeoffs and recovery logicNever represented as a real system, target, performance figure, or forecast

Report promotion and .uai routing

Every uploaded report is stored under /docs/long-term-memory/reports with a stable ID and exact SHA-256 digest. The .uai long-term-memory ledger points to every body. Subject-specific conclusions are compacted into the memory file that owns them—architecture, constraints, context, decisions, or report synthesis—rather than copying full reports into startup memory.

A research-input label means the report is preserved and useful. It does not mean every claim is independently verified, current, or suitable for a concise public answer.

Synthetic model

The Explorer, scenarios, ACK Lab, interoperability checks, and authority controls use fictional nodes, abstract capabilities, illustrative scores, and deterministic rules. They are designed to teach structure, evidence, authority, and graceful degradation.

They do not model real targets, unit locations, weapon performance, casualty outcomes, operational latency, or command decisions.

Safety and non-operational boundary

  • No real targets, exact operational coordinates, active unit locations, or vulnerable infrastructure
  • No casualty assumptions, destructive-efficiency scoring, or weapon construction
  • No functional malware, exploit commands, credential harvesting, or arbitrary external actions
  • No ranking of countries, systems, or organizations by lethality or simulated harm
  • No browser access to private .uai memory, internal reports outside the allowlisted controller, credentials, or unpublished files

Corrections and limitations

Readers can report an error using the public contact address. Corrections should identify the page, claim, source, and reason. The release line records accepted changes.

Public information about military systems is incomplete by design. The site distinguishes documented public facts, analytical synthesis, illustrative engineering values, allegations or disputes, and public unknowns.

Implementation basis: KW-RPT-001; doctrinal comparison basis: KW-RPT-014.

Answer-ready summary

Direct answers

What does Methodology cover?

Review the site’s evidence hierarchy, report-promotion rules, synthetic-model boundary, source labels, limitations, and correction process.

Read the supporting page